TY - JOUR A1 - Kiefl, Sophia A1 - Fischer, Sophie A1 - Schmitt, Jan T1 - Self-employed and stressed out? The impact of stress and stress management on entrepreneurs’ mental health and performance JF - Frontiers in Psychology N2 - Introduction: Entrepreneurs play a central role in economic and social stability, yet the start-up rate in Germany has declined in recent years, possibly due to the stress associated with entrepreneurial endeavors. Stressors such as financial uncertainty and time pressure are prevalent among entrepreneurs and negatively affect their psychological well-being. However, research on stress management strategies among self-employed individuals remains limited. Methods: This pilot study conducted a quantitative analysis with 117 self-employed participants in Germany. The study focused on typical entrepreneurial work demands and selected stress coping mechanisms. Results: The analysis revealed a significant correlation between quantitative demands and mental exhaustion. Furthermore, a high positive correlation between presenteeism and workload suggests that presenteeism may partially explain the variance in workload. These findings underscore how high job demands can lead to self-endangering behaviors that are detrimental to mental health. Discussion: Although no significant moderating effect of proactive coping on the relationship between job demands and mental exhaustion was observed, significant negative correlations between proactive coping and both job demands and mental exhaustion suggest a potential protective role of proactive coping against work-related stress. This study highlights the importance of understanding stress coping strategies among self-employed individuals and their impact on entrepreneurial success and mental well-being. Further research in this area is warranted to develop effective interventions to support the well-being and productivity of self-employed individuals in Germany. KW - General Psychology Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-55955 SN - 1664-1078 VL - 15 PB - Frontiers Media SA ER - TY - JOUR A1 - Maximilian, Rosilius A1 - Spiertz, Martin A1 - Wirsing, Benedikt A1 - Geuen, Manuel A1 - Bräutigam, Volker A1 - Ludwig, Bernd T1 - Impact of Industrial Noise on Speech Interaction Performance and User Acceptance when Using the MS HoloLens 2 JF - Multimodal Technologies and Interaction Y1 - 2024 U6 - https://doi.org/10.3390/mti8020008 VL - 8 ER - TY - JOUR A1 - Kiefl, Sophia A1 - Fischer, Sophie A1 - Schmitt, Jan T1 - Self-employed and stressed out? The impact of stress and stress management on entrepreneurs’ mental health and performance JF - Frontiers in Psychology Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-56040 VL - 15 PB - Frontiers ER - TY - JOUR A1 - Höfflin, Dennis A1 - Sauer, Christian A1 - Schiffler, Andreas A1 - Hartmann, Jürgen T1 - Process Monitoring Using Synchronized Path Infrared Thermography in PBF-LB/M JF - Sensors N2 - Additive manufacturing processes, particularly Laser-Based Powder Bed Fusion of Metals (PBF-LB/M), enable the development of new application possibilities due to their manufacturing-specific freedom of design. These new fields of application require a high degree of component quality, especially in safety-relevant areas. This is currently ensured primarily via a considerable amount of downstream quality control. Suitable process monitoring systems promise to reduce this effort drastically. This paper introduces a novel monitoring method in order to gain process-specific thermal information during the manufacturing process. The Synchronized Path Infrared Thermography (SPIT) method is based on two synchronized galvanometer scanners allowing high-speed and high-resolution observations of the melt pool in the SWIR range. One scanner is used to steer the laser over the building platform, while the second scanner guides the field of view of an IR camera. With this setup, the melting process is observed at different laser powers, scan speeds and at different locations with respect to the laser position, in order to demonstrate the positioning accuracy of the system and to initially gain thermal process data of the melt pool and the heat-affected zone. Therefore, the SPIT system shows a speed independent overall accuracy of ±2 Pixel within the evaluated range. The system further allows detailed thermal observation of the melt pool and the surrounding heat-affected zone. KW - SPIT KW - PBF-LB/M KW - additive manufacturing KW - process monitoring KW - SWIR KW - melt pool KW - galvanometer scanner Y1 - 2022 U6 - https://doi.org/10.3390/s22165943 VL - 22 IS - 16 PB - MDPI ER - TY - JOUR A1 - Cherif, Eya A1 - Hell, Maximilian A1 - Brandmeier, Melanie T1 - DeepForest: novel deep learning models for land use and land cover classification using multi-temporal and -modal sentinel data of the amazon basin JF - Remote Sensing N2 - Land use and land cover (LULC) mapping is a powerful tool for monitoring large areas. For the Amazon rainforest, automated mapping is of critical importance, as land cover is changing rapidly due to forest degradation and deforestation. Several research groups have addressed this challenge by conducting local surveys and producing maps using freely available remote sensing data. However, automating the process of large-scale land cover mapping remains one of the biggest challenges in the remote sensing community. One issue when using supervised learning is the scarcity of labeled training data. One way to address this problem is to make use of already available maps produced with (semi-) automated classifiers. This is also known as weakly supervised learning. The present study aims to develop novel methods for automated LULC classification in the cloud-prone Amazon basin (Brazil) based on the labels from the MapBiomas project, which include twelve classes. We investigate different fusion techniques for multi-spectral Sentinel-2 data and synthetic aperture radar Sentinel-1 time-series from 2018. The newly designed deep learning architectures—DeepForest-1 and DeepForest-2—utilize spatiotemporal characteristics, as well as multi-scale representations of the data. In several data scenarios, the models are compared to state-of-the-art (SotA) models, such as U-Net and DeepLab. The proposed networks reach an overall accuracy of up to 75.0%, similar to the SotA models. However, the novel approaches outperform the SotA models with respect to underrepresented classes. Forest, savanna and crop were mapped best, with F1 scores up to 85.0% when combining multi-modal data, compared to 81.6% reached by DeepLab. Furthermore, in a qualitative analysis, we highlight that the classifiers sometimes outperform the inaccurate labels. KW - deep learning KW - land use and land cover classification KW - multi-modal and multi-temporal data Y1 - 2022 U6 - https://doi.org/10.3390/rs14195000 SN - 2072-4292 VL - 14 IS - 19 ER - TY - JOUR A1 - Engelmann, Bastian A1 - Schmitt, Anna-Maria A1 - Theilacker, Lukas A1 - Schmitt, Jan T1 - Implications from Legacy Device Environments on the Conceptional Design of Machine Learning Models in Manufacturing JF - Journal of Manufacturing and Materials Processing Y1 - 2024 UR - https://doi.org/10.3390/jmmp8010015 VL - 2024 ER - TY - JOUR A1 - Engelmann, Bastian A1 - Schmitt, Anna-Maria A1 - Heusinger, Moritz A1 - Borysenko, Vladyslav A1 - Niedner, Niklas A1 - Schmitt, Jan T1 - Detecting Changeover Events on Manufacturing Machines with Machine Learning and NC data JF - Applied Artificial Intelligence Y1 - 2024 UR - https://doi.org/10.1080/08839514.2024.2381317 PB - Taylor & Francis ER - TY - JOUR A1 - Schmitt, Anna-Maria A1 - Miller, Eddi A1 - Engelmann, Bastian A1 - Batres, Rafael A1 - Schmitt, Jan T1 - G-code evaluation in CNC milling to predict energy consumption through Machine Learning JF - Advances in Industrial and Manufacturing Engineering N2 - Computerized Numeric Control (CNC) plays an essential role in highly autonomous manufacturing systems for interlinked process chains for machine tools. NC-programs are mostly written in standardized G-code. Evaluating CNC-controlled manufacturing processes before their real application is advantageous due to resource efficiency. One dimension is the estimation of the energy demand of a part manufactured by an NC-program, e.g. to discover optimization potentials. In this context, this paper presents a Machine Learning (ML) approach to assess G-code for CNC-milling processes from the perspective of the energy demand of basic G-commands. We propose Latin Hypercube Sampling as an efficient method of Design of Experiments to train the ML model with minimum experimental effort to avoid costly setup and implementation time of the model training and deployment. KW - Machine Learning KW - CNC machine tools KW - G-code KW - Energy consumption Y1 - 2024 UR - https://doi.org/10.1016/j.aime.2024.100140 VL - 2024 IS - 8 ER - TY - JOUR A1 - Scheller, Fabian T1 - The future demand of renewable fuels in Germany - Understanding the impact of electrification levels and socio-economic developments JF - Heliyon N2 - The Climate Change Act recently enacted in Germany highlights the urgency of understanding the future demand for renewable fuels. In this study, we combine technological progress and socio-economic pathways in an energy system analysis to assess future renewable fuel demands in Germany. We apply the whole-system optimisation model, TIMES, to investigate transition pathways with varying electrification levels and socio-economic developments. The results show that renewable fuels demand varies between 388 PJ and 1310 PJ depending on the electrification rates. Furthermore, our findings demonstrate that considering socio-economicaspects and behavioural change, as represented by different Shared-Socio-economic Pathways, can significantly alter the demand for renewable fuels within a narrower yet still noteworthy range compared to the electrification scenarios. This provides country-level evidence highlighting the often-overlooked influence of social developments on demand projections. Consequently, it becomes crucial to prioritize the consideration of the climate mitigation potential arising fromsocioeconomic-induced changes in demand patterns within the broader framework of energyefficiency measures. Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-53637 VL - 9 IS - 11 PB - Elsevier ER - TY - JOUR A1 - Kleibl, Tanja A1 - Xypolytas, Nikos T1 - Oppression or liberation? The function of social work in migration management N2 - Drawing on the work of Antonio Gramsci and liberation scholars from Latin America, this article examines the role of social work, as both an academic discipline and a practice, in the context of the recent refugee crisis. This role mirrors the historical development of social work and is further highlighted by recent empirical studies of refugee experiences on Greek islands. The authors call for an active political coalition between social work practitioners and refugees, with the aim of empowering the latter in their quest for liberation from the regime of European refugee management. N2 - Auf der Grundlage der Arbeiten von Antonio Gramsci und lateinamerikanischen Befreiungstheoretiker:innen untersucht der Artikel die Rolle der Sozialen Arbeit, sowohl als akademische Disziplin als auch als Praxis, im Zusammenhang mit der jüngsten Flüchtlingskrise. Diese Rolle spiegelt die historische Entwicklung der Sozialen Arbeit wider und wird anhand der jüngsten empirischen Erfahrungen mit Geflüchteten auf den griechischen Inseln weiter verdeutlicht. Die Autor:innen rufen zu einer aktiven politischen Koalition zwischen Sozialarbeiter:innen und Geflüchteten auf, mit dem Ziel, letztere in ihrem Streben nach Befreiung vom Regime des europäischen Flüchtlingsmanagements zu stärken. Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-56389 UR - https://regener-online.de/journalcco/2022_2/pdf/kleibl-xypolytas2022.pdf N1 - © 2022 by verlag irena regener berlin VL - 21 IS - 2 PB - Regener ER - TY - JOUR A1 - Schmitt, Jan A1 - Engelmann, Bastian A1 - Manghisi, Vito Modesto A1 - Wilhelm, Markus A1 - Uva, Antonello A1 - Fiorentino, Michele T1 - Towards gestured-based technologies for human-centred smart factories JF - International Journal of Computer Integrated Manufacturing N2 - Despite the increasing degree of automation in industry, manual or semi-automated are commonly and inevitable for complex assembly tasks. The transformation to smart processes in manufacturing leads to a higher deployment of data-driven approaches to support the worker. Upcoming technologies in this context are oftentimes based on the gesture-recognition, − monitoring or – control. This contribution systematically reviews gesture or motion capturing technologies and the utilization of gesture data in the ergonomic assessment, gesture-based robot control strategies as well as the identification of COVID-19 symptoms. Subsequently, two applications are presented in detail. First, a holistic human-centric optimization method for line-balancing using a novel indicator – ErgoTakt – derived by motion capturing. ErgoTakt improves the legacy takt-time and helps to find an optimum between the ergonomic evaluation of an assembly station and the takt-time balancing. An optimization algorithm is developed to find the best-fitting solution by minimizing a function of the ergonomic RULA-score and the cycle time of each assembly workstation with respect to the workers’ ability. The second application is gesture-based robot-control. A cloud-based approach utilizing a generally accessible hand-tracking model embedded in a low-code IoT programming environment is shown. KW - gesture-based monitoring KW - gesture-based control KW - manufacturing Y1 - 2023 UR - https://doi.org/10.1080/0951192X.2022.2121424 SN - 1362-3052 VL - 36 IS - 1 SP - 110 EP - 127 ER - TY - JOUR A1 - Schmitt, Jan A1 - Seitz, Philipp A1 - Scherdel, Christian A1 - Reichenauer, Gudrun T1 - Machine Learning in the development of Si-based anodes using Small-Angle X-ray Scattering for structural property analysis JF - Computational Materials Science N2 - Material development processes are highly iterative and driven by the experience and intuition of the researcher. This can lead to time consuming procedures. Data-driven approaches such as Machine Learning can support decision processes with trained and validated models to predict certain output parameter. In a multifaceted process chain of material synthesis of electrochemical materials and their characterization, Machine Learning has a huge potential to shorten development processes. Based on this, the contribution presents a novel approach to utilize data derived from Small-Angle X-ray Scattering (SAXS) of SiO_2 matrix materials for battery anodes with Neural Networks. Here, we use SAXS as an intermediate, high-throughput method to characterize sol–gel based porous materials. A multi-step-method is presented where a Feed Forward Net is connected to a pretrained autoencoder to reliably map parameters of the material synthesis to the SAXS curve of the resulting material. In addition, a direct comparison shows that the prediction error of Neural Networks can be greatly reduced by training each output variable with a separate independent Neural Network. KW - machine learning KW - neural network KW - autoencoder Y1 - 2023 UR - https://doi.org/10.1016/j.commatsci.2022.111984 SN - 1879-0801 N1 - Link zum Datensatz: https://gitlab.vlab.fm.fhws.de/philipp.seitz/machinelearningandsaxs VL - 218 ER - TY - JOUR A1 - Konrad, Robert A1 - Güttler, Carina A1 - Öhl, Natalie A1 - Heidl, Christian A1 - Scholz, Stefanie A1 - Bauer, Christian T1 - Effects of the Tovertafel® on apathy, social interaction and social activity of people with dementia in long-term inpatient care BT - Results of a non-controlled within-subject-design study JF - Frontiers in Neurology N2 - Introduction: Tovertafel® is a VR-based serious game for dementia care (SGDC) that aims to stimulate residents affected by dementia in nursing homes, promote social and cognitive skills and reduce apathy. The aim of this study is to investigate the effects of using Tovertafel® on apathy, social interaction and social activity of people with dementia (PWD) in long-term inpatient care in Germany. Methods: In this monocentric intervention study, 25 residents of an inpatient long-term care facility with moderate or severe dementia had two weekly applications of Tovertafel® over a period of 8 weeks. Effects on the residents’ social interaction and activity were recorded before (T1), during (T2) and 1 h after (T3) each intervention using the Engagement of a Person with Dementia Scale (EPWDS). The degree of apathy was assessed using the Apathy Evaluation Scale (AES). Effects of Tovertafel® were examined using a simple repeated measures analysis of variance (ANOVA). Results: Thirteen residents with moderate (52%) and 12 residents with severe dementia (48%) were included. Results showed that residents’ apathy changed over the course of the trial and was partially reduced. ANOVA revealed significant changes in the positive expression of social participation in the overall group between individual observation times (p < 0.001; T1: MW = 2.67, SD = 1.352; T2: MW = 3.66, SD = 1.365; T3: MW = 3.10, SD = 1.300) and a significantly lower negative expression of social participation at T2 (MW = 1.09, SD = 0.358) than at T1 (MW = 1.19, SD = 0.579; p = 0.028). There was a significantly higher positive expression of behavioral involvement in the overall group at T3 (MW = 1.17, SD = 0.552) than at T1 (p = 0.003) or T2 (p = 0.045). Analyses did not find any significant interaction between observation times and degree of dementia. Discussion: Results of the study show that the use of Tovertafel® over a period of 2 months had significant effects on apathy, social activity and social interaction in people with moderate or severe dementia. Symptoms of apathy could be reduced and social interaction and activity increased. However, due to limitations of the study design and special circumstances of the COVID-19 pandemic situation, findings might be overestimated and must be interpreted with care. Further research is necessary. KW - Tovertafel KW - dementia KW - apathy KW - social interaction KW - EPWDS KW - AES KW - SGDC Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-57736 VL - 15 PB - Frontiers ER - TY - JOUR A1 - Schirmer, Fabian A1 - Kranz, Philipp A1 - Rose, Chad G. A1 - Schmitt, Jan A1 - Kaupp, Tobias T1 - Towards Dynamic Human–Robot Collaboration: A Holistic Framework for Assembly Planning JF - Electronics N2 - The combination of human cognitive skills and dexterity with the endurance and repeatability of robots is a promising approach to modern assembly. However, efficiently allocating tasks and planning an assembly sequence between humans and robots is a manual, complex, and time-consuming activity. This work presents a framework named “Extract–Enrich–Assess–Plan–Review” that facilitates holistic planning of human–robot assembly processes. The framework automatically Extracts data from heterogeneous sources, Assesses the suitability of each assembly step to be performed by the human or robot, and Plans multiple assembly sequence plans (ASP) according to boundary conditions. Those sequences allow for a dynamic adaptation at runtime and incorporate different human–robot interaction modalities that are Synchronized, Cooperative, or Collaborative. An expert remains in the loop to Enrich the extracted data, and Review the results of the Assess and Plan steps with options to modify the process. To experimentally validate this framework, we compare the achieved degree of automation using three different CAD formats. We also demonstrate and analyze multiple assembly sequence plans that are generated by our system according to process time and the interaction modalities used. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-57825 SN - 2079-9292 VL - 14 IS - 1 PB - MDPI ER - TY - JOUR A1 - Vobig, Bastian T1 - A Computational Approach to Interaction Type Analysis of Music Therapy Improvisations JF - Music & Science N2 - Improvisation in music therapy is a highly complex and diverse form of creativity, offering a wide variety of musical information for music therapists to work with. To address this diversity in research and analysis, it is common to combine a wide range of interdisciplinary scientific approaches. Microanalysis methods in music therapy provide highly insightful results on a detailed musical level in musical improvisation but come at the cost of a time-consuming analysis procedure. The automation of these methods in machine learning environments and the use of the wealth of digitally obtainable musical information in clinical improvisations is highly promising for enabling the efficient use of microanalytic methods in clinical practice. In particular, assessment procedures – the systematic collection and analysis of client information to plan subsequent therapy sessions – can benefit greatly from a microanalytic insight into imitation patterns or entrainment processes as observable in musical instrument digital interface (MIDI) data. However, the automation of microanalytic methods poses a challenge in formalising analytical arguments while at the same time maintaining qualitative validity in a machine learning environment. This article provides an interdisciplinary theoretical framework for the microanalysis of musical data in clinical improvisation that is suitable for computational implementation, leading to the development of an automated analysis tool for further use in research and clinical practice. While a pilot application of the system presented in the article suggests general functionality, future challenges for the training of a supervised classification model have been identified that focus on the need for formalisation of microanalytic arguments and feature development to ensure qualitative validity. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-58391 SN - 2059-2043 VL - 8 PB - SAGE Publications ER - TY - CHAP A1 - Schirmer, Fabian A1 - Kranz, Philipp A1 - Schmitt, Jan A1 - Kaupp, Tobias T1 - Anomaly Detection for Dynamic Human-Robot Assembly: Application of an LSTM-based autoencoder to interpret uncertain human behavior in HRC T2 - Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction Y1 - 2023 U6 - https://doi.org/10.1145/3568294.3580100 SP - 881 EP - 883 ER - TY - JOUR A1 - Seitz, Philipp A1 - Schmitt, Jan T1 - Alternating Transfer Functions to Prevent Overfitting in Non-Linear Regression with Neural Networks JF - Journal of Experimental & Theoretical Artificial Intelligence N2 - In nonlinear regression with machine learning methods, neural networks (NNs) are ideally suited due to their universal approximation property, which states that arbitrary nonlinear functions can thereby be approximated arbitrarily well. Unfortunately, this property also poses the problem that data points with measurement errors can be approximated too well and unknown parameter subspaces in the estimation can deviate far from the actual value (so-called overfitting). Various developed methods aim to reduce overfitting through modifications in several areas of the training. In this work, we pursue the question of how an NN behaves in training with respect to overfitting when linear and nonlinear transfer functions (TF) are alternated in different hidden layers (HL). The presented approach is applied to a generated dataset and contrasted to established methods from the literature, both individually and in combination. Comparable results are obtained, whereby the common use of purely nonlinear transfer functions proves to be not recommended generally. KW - Machine learning; nonlinear regression; function approximation; overfitting; transfer function Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-49199 UR - https://doi.org/10.1080/0952813X.2023.2270995 ER - TY - JOUR A1 - Weber, Aleksej A1 - Wilhelm, Markus A1 - Schmitt, Jan T1 - Analysis of Factors Influencing the Precision of Body Tracking Outcomes in Industrial Gesture Control JF - sensors N2 - The body tracking systems on the current market offer a wide range of options for tracking the movements of objects, people, or extremities. The precision of this technology is often limited and determines its field of application. This work aimed to identify relevant technical and environmental factors that influence the performance of body tracking in industrial environments. The influence of light intensity, range of motion, speed of movement and direction of hand movement was analyzed individually and in combination. The hand movement of a test person was recorded with an Azure Kinect at a distance of 1.3 m. The joints in the center of the hand showed the highest accuracy compared to other joints. The best results were achieved at a luminous intensity of 500 lx, and movements in the x-axis direction were more precise than in the other directions. The greatest inaccuracy was found in the z-axis direction. A larger range of motion resulted in higher inaccuracy, with the lowest data scatter at a 100 mm range of motion. No significant difference was found at hand velocity of 370 mm/s, 670 mm/s and 1140 mm/s. This study emphasizes the potential of RGB-D camera technology for gesture control of industrial robots in industrial environments to increase efficiency and ease of use. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-57575 VL - 24 IS - 18 PB - MDPI ER - TY - JOUR A1 - Wilhelm, Markus A1 - Lotter, Frank A1 - Scherdel, Christian A1 - Schmitt, Jan T1 - Advancing Efficiency in Mineral Construction Materials Recycling: A Comprehensive Approach Integrating Machine Learning and X-ray Diffraction Analysis JF - buildings N2 - In the context of environmental protection, the construction industry plays a key role with significant CO2 emissions from mineral-based construction materials. Recycling these materials is crucial, but the presence of hazardous substances, i.e., in older building materials, complicates this effort. To be able to legally introduce substances into a circular economy, reliable predictions within minimal possible time are necessary. This work introduces a machine learning approach for detecting trace quantities (≥0.06 wt%) of minerals, exemplified by siderite in calcium carbonate mixtures. The model, trained on 1680 X-ray powder diffraction datasets, provides dependable and fast predictions, eliminating the need for specialized expertise. While limitations exist in transferability to other mineral traces, the approach offers automation without expertise and a potential for real-world applications with minimal prediction time. KW - Architecture KW - Building and Construction KW - Civil and Structural Engineering Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-56030 SN - 2075-5309 VL - 14 IS - 2 PB - MDPI ER - TY - JOUR A1 - Lang, Silvio A1 - Engelmann, Bastian A1 - Schiffler, Andreas A1 - Schmitt, Jan T1 - A simplified machine learning product carbon footprint evaluation tool JF - Cleaner Environmental Systems N2 - On the way to climate neutrality manufacturing companies need to assess the Carbon dioxide (CO2) emissions of their products as a basis for emission reduction measures. The evaluate this so-called Product Carbon Footprint (PCF) life cycle analysis as a comprehensive method is applicable, but means great effort and requires interdisciplinary knowledge. Nevertheless, assumptions must still be made to assess the entire supply chain. To lower these burdens and provide a digital tool to estimate the PCF with less input parameter and data, we make use of machine learning techniques and develop an editorial framework called MINDFUL. This contribution shows its realization by providing the software architecture, underlying CO2 factors, calculations and Machine Learning approach as well as the principles of its user experience. Our tool is validated within an industrial case study. KW - Management, Monitoring, Policy and Law KW - Environmental Science (miscellaneous) KW - Renewable Energy, Sustainability and the Environment KW - Environmental Engineering Y1 - 2024 U6 - https://doi.org/10.1016/j.cesys.2024.100187 SN - 2666-7894 VL - 13 PB - Elsevier BV ER - TY - CHAP A1 - Pfeuffer, Katharina A1 - Fischer, Sophie A1 - Schmitt, Jan A1 - Bräutigam, Volker T1 - Human or Robot Resource Management? The Future of Work in the Digital Transformation of Manufactoring Companies T2 - Proceedings of the Conference on Production Systems and Logistics: CPSL 2025 N2 - This article examines the transformative effects of Smart Factory technologies - such as human-robot collaboration, intelligent assistance systems and cyber-physical production systems - on organizational design, with a particular focus on central fields of action for Human Resources management (HRM) and operational management. A case study of a German automotive supplier is used to examine how digitalization and automation are changing human work and organizational structures. Two future scenarios for organizational models are proposed: the swarm organization, which consists exclusively of highly qualified employees while robots take over routine tasks, and the polarized organization, which is characterized by a division between highly qualified specialists and low-skilled employees. Each scenario brings different challenges and opportunities for HR management, as companies need to adapt to digital skills, new models of collaboration and the management of a highly specialized or polarized workforce. This paper provides a conceptual framework and actionable insights for HRM and production management to manage the shift towards advanced, automated organizational models and ensure a smooth transition to the Smart Factory of the future. Y1 - 2025 U6 - https://doi.org/10.15488/18885 PB - publish-Ing. CY - Offenburg ER - TY - JOUR A1 - Drenkard, Hannah A1 - Fischer, Christian A1 - Sauer, Veit A1 - Gehlen, Christoph T1 - On the Chloride Distribution in Concrete and Mortar Samples after an RCM Test JF - Materials N2 - It is of essential need to face the challenges of CO2 reduction in industrial cement and concrete production reliable test methods in order to evaluate the performance of concretes, especially with regard to the service life of our infrastructure. The rapid chloride migration test (RCM test) is a standard method to assess the resistance against chloride ingress of concrete. However, during our study, certain critical questions arose with regard to the chloride distribution. The sharp chloride ingress front based on the model assumptions contradicted the shallow gradient of the experimental data. For this reason, investigations on chloride distribution in concrete and mortar samples after RCM tests were performed. The focus was on the factors influencing the extraction, e.g., time after RCM test and the location on sample. Furthermore, differences between concrete and mortar samples were investigated. The investigations showed that no sharp gradient on concrete samples was found due to the extremely uneven chloride front. In contrast, the theoretical profile shape was instead demonstrated on mortar specimens. The prerequisite for this result is that the drill powder must be taken directly after the completion of the RCM test from very uniform penetration areas. Thus, the model assumptions on the chloride distribution via the RCM test could be confirmed. KW - chloride profile; RCM test; drill powder; concrete; mortar; chloride migration coefficient; chloride ingress front Y1 - 2023 U6 - https://doi.org/10.3390/ma16082952 SN - 1996-1944 VL - 16 IS - 8 SP - 2952 EP - 2952 ER - TY - JOUR A1 - Höfflin, Dennis A1 - Sauer, Christian A1 - Schiffler, Andreas A1 - Manara, Jochen A1 - Hartmann, Jürgen T1 - Pixelwise high-temperature calibration for in-situ temperature measuring in powder bed fusion of metal with laser beam JF - Heliyon N2 - High-temperature calibration methods in additive manufacturing involve the use of advanced techniques to accurately measure and control the temperature of the build material during the additive manufacturing process. Infrared cameras, blackbody radiation sources and non-linear optimization algorithms are used to correlate the temperature of the material with its emitted thermal radiation. This is essential for ensuring the quality and repeatability of the final product. This paper presents the calibration procedure of an imaging system for in-situ measurement of absolute temperatures and temperature gradients during powder bed fusion of metal with laser beam (PBF-LB/M) in the temperature range of 500 K–1500 K. It describes the design of the optical setup to meet specific requirements in this application area as well as the procedure for accounting the various factors influencing the temperature measurement. These include camera-specific effects such as varying spectral sensitivities of the individual pixels of the sensor as well as influences of the exposure time and the exposed sensor area. Furthermore, influences caused by the complex optical path, such as inhomogeneous transmission properties of the galvanometer scanner as well as angle-dependent transmission properties of the f-theta lens were considered. A two-step fitting algorithm based on Planck's law of radiation was applied to best represent the correlation. With the presented procedure the calibrated thermography system provides the ability to measure absolute temperatures under real process conditions with high accuracy. Y1 - 2024 U6 - https://doi.org/10.1016/j.heliyon.2024.e28989 SN - 2405-8440 VL - 10 IS - 7 PB - Elsevier BV ER - TY - JOUR A1 - Martinez, Mario A1 - Schmitt, Anna-Maria A1 - Schiffler, Andreas A1 - Engelmann, Bastian T1 - Production Data Set for five-Axis CNC Milling with multiple Changeovers JF - Scientific Data N2 - Abstract This data descriptor contains information about an extensive production data set for a five-axis CNC milling process. Three geometrically different products were manufactured and relevant features from the numerical control of the machine were recorded. The recorded manufacturing process contains the preparation of the machine for the next product (changeover) as well as the machining process (production). The experimental manufacturing was organized with the aid of a changeover matrix to ensure that all possible changeover combinations for the three products were considered. The production was repeated five times, resulting in 30 manufacturing sessions and five complete changeover matrices. The data set was recorded in a laboratory environment. A rich feature set including i.e. the NC-code of the products, tool information, and a Jupyter notebook is provided with the data set. Y1 - 2025 U6 - https://doi.org/https://doi.org/10.1038/s41597-025-05294-0 SN - 2052-4463 VL - 12 IS - 1 PB - Springer Science and Business Media LLC ER - TY - JOUR A1 - Henking, Tanja T1 - Die Reform des Betreuungsrechts T1 - The reform of guardianship law JF - Der Nervenarzt N2 - Die Betreuungsrechtsreform ist beschlossen! Zum 01.01.2023 tritt sie in Kraft. Das Betreuungsrecht wird in seiner inhaltlichen Ausrichtung nicht völlig neu aufgestellt. Das Spannungsverhältnis zwischen dem Schutz der Person vor einer nicht eigenverantwortlichen Entscheidung und der Selbstbestimmung der Person wird konsequent weitergedacht und die Selbstbestimmung der betroffenen Person gestärkt. Unterstützende Entscheidungsfindung, die Befolgung von Wünschen und die Aufgabe des Begriffs „Wohl“ als Maßstab für das Betreuerhandeln sind einige Beispiele hierfür. Das neue Recht zieht auch Grenzen bei der Befolgung von Wünschen. Nämlich dann, wenn mit ihnen die Gefahr einer erheblichen Schädigung der Person oder ihres Vermögens einhergeht. Der Beitrag stellt zunächst wesentliche Ziele der Reform dar. Hiervon ausgehend werden Schwerpunkte gesetzt, die für die psychiatrische Praxis relevant erscheinen: die Streichung des Worts „Wohl“, die Regelung der Vorsorgevollmacht, Maßnahmen zur stärkeren Beachtung und zur besseren Umsetzung des im Betreuungsrecht zentralen Grundsatzes der Erforderlichkeit. Kritisch wird Stellung bezogen zum neu eingefügten Ehegattenvertretungsrecht. Im Ergebnis bleibt festzustellen, dass im Bereich der Gesundheitssorge und erst recht im Bereich der Zwangsmaßnahmen für die Praxis recht wenig bedeutsame Änderungen eintreten werden. Ob sich das begrüßenswerte Anliegen des Gesetzgebers verwirklicht, Betreuungen durch eine verbesserte Information und Beratung zu sozialen Rechten und Ansprüchen zu vermeiden, wird die Praxis erst noch zeigen müssen. Gleiches gilt sicherlich auch für eine Stärkung der Entscheidungsunterstützung, eine Idee, die ebenfalls zu begrüßen ist, für die die Praxis aber noch nach einem Goldstandard sucht. N2 - The reform of the guardianship law has been decided! The reform will come into force on 1 January 2023. The content of the guardianship law will not be completely restructured. The tense relationship between the protection of the person against decisions not made on his or her own responsibility and the self-determination of the person will be consistently further considered and strengthened in favor of the self-determination of the person concerned. Supportive decision making, the consideration of a person’s wishes, the abandonment of the term (and concept of) “well-being” as a measure for guardianship are some examples; however, the new law also sets boundaries in adhering to a person’s wishes. Namely, if they are associated with the risk of significant harm to the person or his or her property. The article first presents the main objectives of the reform. Based on this, the focal points are the deletion of the word “well-being”, the regulation of the proxy power of attorney and measures for greater consideration and better implementation of the principle of the necessity, which is central to the guardianship law. Critical comments are made on the newly introduced spousal representation law and its significance for the psychiatric practice. As a result, it can be stated that there will be hardly any significant changes in healthcare and even less so in the area of coercive measures. It remains to be seen whether the legislator’s welcome concern to avoid guardianship through improved information and counselling on social rights will be achieved in practice. The same certainly applies to the strengthening of supported decision making, the idea of which is also to be welcomed but is still looking for a gold standard for practice. KW - Entscheidungsunterstützung KW - Supported decision-making Y1 - 2023 UR - https://doi.org/10.1007/s00115-022-01355-6 SN - 1433-0407 VL - 93 SP - 1125 EP - 1133 ER - TY - JOUR A1 - Höfflin, Dennis A1 - Hartmann, Jürgen A1 - Rosilius, Maximilian A1 - Seitz, Philipp A1 - Schiffler, Andreas T1 - Opto-Thermal Investigation of Additively Manufactured Steel Samples as a Function of the Hatch Distance JF - Sensors N2 - Nowadays, additive manufacturing processes are becoming more and more appealing due to their production-oriented design guidelines, especially with regard to topology optimisation and minimal downstream production depth in contrast to conventional technologies. However, a scientific path in the areas of quality assurance, material and microstructural properties, intrinsic thermal permeability and dependent stress parameters inhibits enthusiasm for the potential degrees of freedom of the direct metal laser melting process (DMLS). Especially in quality assurance, post-processing destructive measuring methods are still predominantly necessary in order to evaluate the components adequately. The overall objective of these investigations is to gain process knowledge make reliable in situ statements about component quality and material properties based on the process parameters used and emission values measured. The knowledge will then be used to develop non-destructive tools for the quality management of additively manufactured components. To assess the effectiveness of the research design in relation to the objectives for further investigations, this pre-study evaluates the dependencies between the process parameters, process emission during manufacturing and resulting thermal diffusivity and the relative density of samples fabricated by DMLS. Therefore, the approach deals with additively built metal samples made on an EOS M290 apparatus with varying hatch distances while simultaneously detecting the process emission. Afterwards, the relative density of the samples is determined optically, and thermal diffusivity is measured using the laser flash method. As a result of this pre-study, all interactions of the within factors are presented. The process variable hatch distance indicates a strong influence on the resulting material properties, as an increase in the hatch distance from 0.11 mm to 1 mm leads to a drop in relative density of 57.4%. The associated thermal diffusivity also reveals a sharp decrease from 5.3 mm2/s to 1.3 mm2/s with growing hatch distances. The variability of the material properties can also be observed in the measured process emissions. However, as various factors overlap in the thermal radiation signal, no clear assignment is possible within the scope of this work. KW - additive manufacturing processes KW - material Y1 - 2021 U6 - https://doi.org/10.3390/s22010046 SN - 1424-8220 VL - 22 IS - 1 PB - MDPI ER - TY - JOUR A1 - Hell, Maximilian A1 - Brandmeier, Melanie T1 - Identifying Plausible Labels from Noisy Training Data for a Land Use and Land Cover Classification Application in Amazônia Legal JF - remote sensing N2 - Most studies in the field of land use and land cover (LULC) classification in remote sensing rely on supervised classification, which requires a substantial amount of accurate label data. However, reliable data are often not immediately available, and are obtained through time-consuming manual labor. One potential solution to this problem is the use of already available classification maps, which may not be the true ground truth and may contain noise from multiple possible sources. This is also true for the classification maps of the MapBiomas project, which provides land use and land cover (LULC) maps on a yearly basis, classifying the Amazon basin into more than 24 classes based on the Landsat data. In this study, we utilize the Sentinel-2 data with a higher spatial resolution in conjunction with the MapBiomas maps to evaluate a proposed noise removal method and to improve classification results. We introduce a novel noise detection method that relies on identifying anchor points in feature space through clustering with self-organizing maps (SOM). The pixel label is relabeled using nearest neighbor rules, or can be removed if it is unknown. A challenge in this approach is the quantification of noise in such a real-world dataset. To overcome this problem, highly reliable validation sets were manually created for quantitative performance assessment. The results demonstrate a significant increase in overall accuracy compared to MapBiomas labels, from 79.85% to 89.65%. Additionally, we trained the L2HNet using both MapBiomas labels and the filtered labels from our approach. The overall accuracy for this model reached 93.75% with the filtered labels, compared to the baseline of 74.31%. This highlights the significance of noise detection and filtering in remote sensing, and emphasizes the need for further research in this area. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-57532 VL - 26 IS - 12 ER - TY - JOUR A1 - Speckenwirth, Sönke A1 - Brandmeier, Melanie A1 - Paczkowski, Sebastian T1 - TreeSeg - A Toolbox for Fully Automated Tree Crown Segmentation Based on High-Resolution Multispectral UAV Data JF - remote sensing N2 - Single-tree segmentation on multispectral UAV images shows significant potential for effective forest management such as automating forest inventories or detecting damage and diseases when using an additional classifier. We propose an automated workflow for segmentation on high-resolution data and provide our trained models in a Toolbox for ArcGIS Pro on our GitHub repository for other researchers. The database used for this study consists of multispectral UAV data (RGB, NIR and red edge bands) of a forest area in Germany consisting of a mix of tree species consisting of five deciduous trees and three conifer tree species in the matured closed canopy stage at approximately 90 years. Information of NIR and Red Edge bands are evaluated for tree segmentation using different vegetation indices (VIs) in comparison to only using RGB information. We trained Faster R-CNN, Mask R-CNN, TensorMask and SAM in several experiments and evaluated model performance on different data combinations. All models with the exception of SAM show good performance on our test data with the Faster R-CNN model trained on the red and green bands and the Normalized Difference Red Edge Index (NDRE) achieving best results with an F1-Score of 83.5% and an Intersection over Union of 65.3% on highly detailed labels. All models are provided in our TreeSeg toolbox and allow the user to apply the pre-trained models on new data. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-57590 VL - 16 IS - 19 PB - MDPI ER - TY - JOUR A1 - Konrad, Robert A1 - Schuster, Denise A1 - Heppner, HJ T1 - Healthcare assessment tools - a valid source of data for pre-hospital care? Usability for ensuring medical care in the event of a disaster JF - Frontiers in Public Health N2 - Providing care for vulnerable population groups in the event of a disaster or evacuation is in the interests of those affected, of local authorities, health insurance companies, other insurance companies and the responsible authorities and organizations with security tasks (BOS). Evacuation and supply planning is currently mostly carried out using regionally or locally adapted so-called “isolated or individual solutions” or by means of an individual, time-consuming and usually manual and direct personal data query. Can existing medical health data from healthcare assessment tools provide valid information for the planning of care and care needs in disaster and civil protection?MethodsResearch and analysis of suitable and regularly used care assessment tools in the care sector in Germany.ResultsThe healthcare assessment tools cannot be simply combined. Without adaptation they cannot be used at all or only after concerted efforts to interpret the needs for the care of vulnerable groups in a non-clinical context.DiscussionAn improved use of individual medical data in disaster and civil protection offers many advantages in prevention, diagnostics, therapy and care in the context of disaster medicine, and not only from an ethical point of view. Due to the different tactical procedures and care strategies in disaster medicine, the field of acute care must be clearly separated from the area of evacuation and care of vulnerable groups. Currently, only the German Armed Forces (Bundeswehr) offer an internally secured infrastructure that allows all those involved in the care of soldiers to access all important medical data quickly and easily from any location. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-57818 SN - 2296-2565 VL - 12 PB - Frontiers ER - TY - JOUR A1 - Brandmeier, Melanie A1 - Heßdörfer, Daniel A1 - Siebenlist, Philipp A1 - Meyer-Spelbrink, Adrian A1 - Kraus, Anja T1 - Time Series Analysis of Multisensor Data for Precision Viticulture BT - Assessing Microscale Variations in Plant Development with Respect to Irrigation and Topography JF - remote sensing N2 - In the context of climate change, vineyard monitoring to better understand spatiotemporal patterns of grapevine development is of utter importance for precision viticulture. We present a time series analysis of hyperspectral in situ and multispectral UAV data for different irrigation systems in Lower Franconia and correlate results with sensor data for soil moisture, temperature, and precipitation. Analysis of Variance (ANOVA) and a Tukey’s HSD test were performed to see whether Vegetation Indices (VIs) are significantly different with respect to irrigation systems as well as topographic position in the vineyard. Correlation between in situ measurements and UAV data for selected VIs is also investigated for upscaling analysis. We find significant differences with respect to irrigation, as well as for topographic position for most of the VIs investigated, highlighting the importance of adapted water management. Correlation between in situ and UAV data is significant only for some indices (NDVI and CIRedEdge, 𝑟2 of 0.33 and 0.49, respectively), while shallow soil moisture patterns correlate well with in situ-derived VIs such as the CIRedEdge and RG index (𝑟2 of 0.34 and 0.46). Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-57527 VL - 16 IS - 8 PB - MDPI ER - TY - JOUR A1 - Manko, Pavlo A1 - Brunn, Ansgar A1 - Melnyk, Oleksandr T1 - Remote sensing methods for estimating tree species of forests in the Volyn region, Ukraine JF - Frontiers in Forests and Global Change N2 - Forest classification is needed to solve a wide range of environmental issues related to of forest classes and succession processes, the extent of afforestation and deforestation and global environmental change. These applications require a very accurate mapping and monitoring of forest types. This article investigates the combination of modern open geographic information systems and remote sensing data in forest management tasks for a specific part of the Ukrainian state area. Based on the existing afforestation plans, the results of the unsupervised classification of Sentinel-2 images and the selection of forest species fragments with closed crowns as training data for supervised classification, classifiers of forest species of the study object were developed with and without taking into account age groups. A supervised classification of research objects is realized and the accuracy of the obtained results is evaluated. It is established that the accuracy of determining forest species on the basis of the proposed method is 90.3 and 91.4%, taking into account age groups and without taking them into account, respectively. Thus, it is found that the modeling of the age groups does not improve the classification result for the test area. KW - remote sensing KW - tree species KW - supervised classification Y1 - 2023 UR - https://doi.org/10.3389/ffgc.2023.1041882 SN - 2624-893X VL - 6 ER - TY - JOUR A1 - Meißner, Pascal A1 - Dillmann, Rüdiger T1 - Implicit Shape Model Trees - Recognition of 3-D Indoor Scenes and Prediction of Object Poses for Mobile Robots JF - robotics N2 - This article describes an approach for mobile robots to identify scenes in configurations of objects spread across dense environments. This identification is enabled by intertwining the robotic object search and the scene recognition on already detected objects. We proposed “Implicit Shape Model (ISM) trees” as a scene model to solve these two tasks together. This article presents novel algorithms for ISM trees to recognize scenes and predict object poses. For us, scenes are sets of objects, some of which are interrelated by 3D spatial relations. Yet, many false positives may occur when using single ISMs to recognize scenes. We developed ISM trees, which is a hierarchical model of multiple interconnected ISMs, to remedy this. In this article, we contribute a recognition algorithm that allows the use of these trees for recognizing scenes. ISM trees should be generated from human demonstrations of object configurations. Since a suitable algorithm was unavailable, we created an algorithm for generating ISM trees. In previous work, we integrated the object search and scene recognition into an active vision approach that we called “Active Scene Recognition”. An efficient algorithm was unavailable to make their integration using predicted object poses effective. Physical experiments in this article show that the new algorithm we have contributed overcomes this problem. Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-53649 VL - 12 IS - 158 PB - MDPI ER - TY - JOUR A1 - Hart, Lukas A1 - Knoblach, Stefan A1 - Möser, Michael T1 - Automated pipeline reconstruction using deep learning & instance segmentation JF - ISPRS Open Journal of Photogrammetry and Remote Sensing N2 - BIM is a powerful tool for the construction industry as well as for various other industries, so that its use has increased massively in recent years. Laser scanners are usually used for the measurement, which, in addition to the high acquisition costs, also cause problems on reflective surfaces. The use of photogrammetric techniques for BIM in industrial plants, on the other hand, is less widespread and less automated. CAD software (for point cloud evaluation) contains at best automated reconstruction algorithms for pipes. Fittings, flanges or elbows require a manual reconstruction. We present a method for automated processing of photogrammetric images for modeling pipelines in industrial plants. For this purpose we use instance segmentation and reconstruct the components of the pipeline directly based on the edges of the segmented objects in the images. Hardware costs can be kept low by using photogrammetry instead of laser scanning. Besides the autmatic extraction and reconstruction of pipes, we have also implemented this for elbows and flanges. For object recognition, we fine-tuned different instance segmentation models using our own training data, while also testing various data augmentation techniques. The average precision varies depending on the object type. The best results were achieved with Mask R–CNN. Here, the average precision was about 40%. The results of the automated reconstruction were examined with regard to the accuracy on a test object in the laboratory. The deviations from the reference geometry were in the range of a few millimeters and were comparable to manual reconstruction. In addition, further tests were carried out with images from a plant. Provided that the objects were correctly and completely recognized, a satisfactory reconstruction is possible with the help of our method. Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-53620 VL - 9 PB - Elsevier ER - TY - JOUR A1 - Gielinger, Sebastian A1 - Hein, Thiemo A1 - Ziegler, Andreas A1 - Oeser, David A1 - Breitfelder, Sebastian A1 - Bohn, Gunther T1 - A Short Time Expansion Measurement Method for the Detection of Aging Effect of Lithium Ion Cells Using a High Resolution Laser Interfometric Setup JF - IEEE Access N2 - In this work a new expansion measurement methodology for the detection of ageing mechanisms in lithium ion cells is described and evaluated. For this purpose, a polarization-optical homodyne Michelson interferometer with a resolution of approx. 10 nm was set up to allow measurements of different cell types, cell sizes, and cell chemistry within a Memmert IP55 climate chamber. The used interferometric measurement setup is ten times more accurate than measurement systems commonly used for battery measurements in the literature. The better spatial resolution of an interferometer setup enables the recording of the expansion response to short current pulses with low transferred charge. This offers the possibility to detect ageing mechanisms such as lithium plating within short measuring times. With this measurement setup, a lithium iron phosphate pouch cell from the company A123, with the model identification AMP20M1HD-A, is measured. First, an expansion measurement over a full charge and discharge cycle with a constant load of ± C 20 (b=1 A) is performed. Here, the cell undergoes an expansion of about 42 μm. Subsequently, the in this work proposed measurement methodology is presented to show the influence of effects such as the formation of overshooting graphite stages or lithium plating on cell expansion. For this purpose, at a residual capacitance of 50%, the cell is pulsed with current of different intensity I ∈ {±20A,±80A} for t = {240 s, 60 s}, at T = {10 ◦C, 20 ◦C, 30 ◦C}, respectively, and the mechanical response is recorded using the high accuracy interferometer setup. A mechanical relaxation of the cell after the pulses with a time constant in the range between 10 s and 20 s can be observed. It is shown that this relaxation behavior can be associated with effects of the anode known from the literature, such as the formation of overshooting graphite stages or lithium plating. These effects can be recorded by the very high-resolution measurement already with little transferred charge and within a short measurement time. Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-53654 VL - 11 PB - IEEE ER - TY - JOUR A1 - Gielinger, Sebastian A1 - Bohn, Gunther A1 - Deinzer, Frank A1 - Linke, Andreas T1 - Investigation of an inline inspection method for the examination of cylinder-like specular surfaces using deflectometry JF - applied sciences N2 - An optical measuring method is presented, with which it is possible to measure and evaluate reflective cylindrical surfaces using a combination of deflectometry and subsequent reconstruction of the surface. The system is set up and tested on rolling elements of cylindrical roller bearings. However, it is not limited to this use case and can be applied to other cylindrical specular surfaces. The system distinguishes itself from existing test methods through the combination of high-resolution three-dimensional defect measurement with a very short recording time, and offers the possibility of introducing tolerance limits in the production of cylindrical specular surfaces. With this method, it is possible to record a defect with the dimensions of 1.3 mm by 1.8 mm within 5 s and to reconstruct the absolute depth. The resolution of the system is below 10 μm in both X- and Y-direction, and is therefore sufficiently accurate to detect typical surface defects such as scratches, dents, or deformations. To validate the measured values of the system, the results of an artificially generated 10.35 μm deep defect location were compared with those of a highly accurate mechanical stylus measurement. KW - automated optical inspection KW - roller bearing KW - line scan camera Y1 - 2023 UR - https://doi.org/10.3390/app12136449 SN - 2076-3417 VL - 12 IS - 13 ER - TY - JOUR A1 - Fischer, Sophie A1 - Göhlich, Michael A1 - Schmitt, Sophie T1 - Adapting to climate change through play? Didactically effective elements of a business simulation game JF - Frontiers in Education N2 - Introduction: The negative consequences of climate change are widespread and have a global impact. An industrialized region of Germany must adapt to the effects of climate change and comply with political regulations. Previous studies indicate that economic actors who are not directly affected by climate change approach climate change mitigation and adaptation primarily based on legal requirements and often feel discouraged by the absence of data-based reports. Addressing this challenge, game-based learning emerges as a promising pathway. Methods: To examine game-based learning’s applicability and potential for climate adaptation, we developed a business simulation game, simultaneously identifying didactically effective elements for managers who would participate in it. Using expert interviews and focus groups, we conducted a qualitative study with three HR developers from larger companies and nine managers and founders of startups to develop a business simulation game on climate adaptation. Based on the Grounded Theory methodology, theoretical coding was used to analyze the qualitative data. Results: The derived core categories indicate that personnel development in companies is evolving in response to economic changes. Individual resources such as motivation (especially for managers), personnel and time play a crucial role in establishing a business game as an educational offering. The identified game elements can also be used theoretically and practically in the development of other educational games. Discussion: We discussed common human resource development measures in companies and compared them with more innovative approaches such as a simulation game. The study underscores the importance of innovative approaches, such as game-based learning, in fostering climate adaptation efforts among economic actors. By integrating theoretical insights with practical applications, our findings provide valuable guidance for the development of educational games aimed at addressing complex challenges like climate change. Further research and implementation of such approaches are essential for promoting proactive climate adaptation strategies within industrialized regions and beyond. KW - Climate adaptation KW - Game-based learning KW - Serious game KW - Human resource development KW - Business game KW - Corporate social responsibility Y1 - 2024 U6 - https://doi.org/10.3389/feduc.2024.1303107 VL - 2024 IS - 9 SP - 01 EP - 17 ER - TY - JOUR A1 - Anwander, Julia A1 - Brandmeier, Melanie A1 - Paczkowski, Sebastian A1 - Neubert, Tarek A1 - Paczkowska, Marta T1 - Evaluating Different Deep Learning Approaches for Tree Health Classification Using High-Resolution Multispectral UAV Data in the Black Forest, Harz Region, and Göttinger Forest JF - Remote Sensing N2 - We present an evaluation of different deep learning and machine learning approaches for tree health classification in the Black Forest, the Harz Mountains, and the Göttinger Forest on a unique, highly accurate tree-level dataset. The multispectral UAV data were collected from eight forest plots with diverse tree species, mostly conifers. As ground truth data (GTD), nearly 1500 tree polygons with related attribute information on the health status of the trees were used. This data were collected during extensive fieldwork using a mobile application and subsequent individual tree segmentation. Extensive preprocessing included normalization, NDVI calculations, data augmentation to deal with the underrepresented classes, and splitting the data into training, validation, and test sets. We conducted several experiments using a classical machine learning approach (random forests), as well as different convolutional neural networks (CNNs)—ResNet50, ResNet101, VGG16, and Inception-v3—on different datasets and classes to evaluate the potential of these algorithms for tree health classification. Our first experiment was a binary classifier of healthy and damaged trees, which did not consider the degree of damage or tree species. The best results of a 0.99 test accuracy and an F1 score of 0.99 were obtained with ResNet50 on four band composites using the red, green, blue, and infrared bands (RGBI images), while VGG16 had the worst performance, with an F1 score of only 0.78. In a second experiment, we also distinguished between coniferous and deciduous trees. The F1 scores ranged from 0.62 to 0.99, with the highest results obtained using ResNet101 on derived vegetation indices using the red edge band of the camera (NDVIre images). Finally, in a third experiment, we aimed at evaluating the degree of damage: healthy, slightly damaged, and medium or heavily damaged trees. Again, ResNet101 had the best performance, this time on RGBI images with a test accuracy of 0.98 and an average F1 score of 0.97. These results highlight the potential of CNNs to handle high-resolution multispectral UAV data for the early detection of damaged trees when good training data are available. KW - tree health KW - classification KW - deep learning KW - CNNs KW - UAV KW - multispectral Y1 - 2024 U6 - https://doi.org/10.3390/rs16030561 VL - 16 IS - 3 SP - 561 EP - 561 ER - TY - JOUR A1 - Yamshchikov, Ivan A1 - Koltun, Vladyslav T1 - Pump It - Twitter Sentiment Analysis for Cryptocurrency Price Prediction JF - Risks Y1 - 2023 U6 - https://doi.org/10.3390/risks11090159 VL - 11 IS - 159 PB - MDPI ER - TY - JOUR A1 - Weiß, Eva-Maria A1 - Unz, Dagmar C. A1 - Schwab, Frank T1 - Scoping Review on the Effects of Simulation-Based Interventions on Reducing Stigma Toward People with Schizophrenia JF - Frontiers in Virtual Reality N2 - Introduction: Schizophrenia imposes a significant burden on global public health and is associated with pervasive stigmatization, perpetuating misconceptions of danger and incompetence. This review examines the efficacy of simulation interventions in reducing stigmas associated with schizophrenia and fostering empathy towards affected individuals. Methods: A comprehensive literature review spanning from August 2021 to September 2022 identified 14 relevant studies meeting inclusion criteria. Results: Analysis revealed a diverse landscape of simulation-based interventions, characterized by variability in methodological rigor, intervention design, and technological modalities. While some studies demonstrated promising outcomes in stigma reduction and empathy enhancement, methodological limitations and inconsistencies underscore the need for cautious interpretation of findings. Furthermore, mixed outcomes in stigma characteristics and empathy development highlight the complexity of intervention effectiveness. Discussion: Despite these challenges, simulation interventions, particularly when integrated with additional components, hold potential in mitigating stigmatization and promoting empathy. Future research should prioritize methodological rigor, comprehensive outcome assessment, and tailored intervention strategies to advance the field of stigma reduction in schizophrenia. KW - Schizophrenia KW - stigma reduction KW - simulation-based intervention KW - virtual reality Y1 - 2025 U6 - https://doi.org/10.3389/frvir.2025.1404156 SN - 2673-4192 VL - 6 PB - Frontiers Media SA ER - TY - JOUR A1 - Endres, Julian A1 - Haas, Tobias A1 - Pawellek, Alexander A1 - Kremer, Vinicius A1 - Franchino, Roger T1 - Evaluation of GaN Transistors for Grid-Connected 3-Level T-Type Inverters JF - Electronics N2 - This paper presents a complete workflow for the evaluation of GaN transistors in voltage source inverters. With the associated high switching speed of transistors based on GaN, it is important to consider some critical points in the design phase as well as in the measurement setup in order to be able to utilise and verify the advantages of GaN properly. For this reason, the presented circuit board’s design focuses on a minimised power loop inductance. Simulation models, an analytical approach and measurement results with the aim of determining this inductance are compared with each other. A good compliance results between the presented methods. Additionally, the description of a test bench is given, which enables the performance of the opposition method. This setup allows the measurement of the designed H-bridge’s arising losses and the GaN-transistor’s switching behaviour. In comparison to the conventional double pulse method, this approach enables results that are more accurate for determining losses. Y1 - 2025 U6 - https://doi.org/https://doi.org/10.3390/electronics14152935 SN - 2079-9292 VL - 14 IS - 15 PB - MDPI ER - TY - JOUR A1 - Raab, Sebastian A1 - Weickert, Sebastian A1 - Kasten, Henning T1 - Methodology for Designing Broadband DC Link Filters for Voltage Source Converters JF - electronics N2 - This paper presents a new methodology for the design process of DC ripple filters for voltage source converters. It focuses on fast-switching, wide-bandgap-material-based converters. Therefore, a wide frequency range of up to 100 MHz is taken into consideration during the whole process. Different tools like analytic calculations, time-domain modelling, and the finite element method are used for different tasks in order to generate a realistic model in terms of filter effect and reliability. The models are validated by small-signal measurements using a vector network analyser as well as realistic high-power tests. The contribution of this paper is to provide a tool for DC link filter design to estimate the filter efficiency and the current stress on the filter elements with a special focus on WBG hardware. Y1 - 2025 U6 - https://doi.org/10.3390/electronics14142743 PB - MDPI ER - TY - JOUR A1 - Bier, Markus T1 - Non-equilibrium steady states of electrolyte interfaces JF - New Journal of Physics N2 - The non-equilibrium steady states of a semi-infinite quasi-one-dimensional univalent binary electrolyte solution, characterised by non-vanishing electric currents, are investigated by means of Poisson-Nernst-Planck (PNP) theory. Exact analytical expressions of the electric field, the charge density and the number density are derived, which depend on the electric current density as a parameter. From a non-equilibrium version of the Grahame equation, which relates the total space charge per cross-sectional area and the corresponding contribution of the electric potential drop, the current-dependent differential capacitance of the diffuse layer is derived. In the limit of vanishing electric current these results reduce to those within Gouy-Chapman theory. It is shown that improperly chosen boundary conditions lead to non-equilibrium steady state solutions of the PNP equations with negative ion number densities. A necessary and sufficient criterion on surface conductivity constitutive relations is formulated which allows one to detect such unphysical solutions. KW - Poisson-Nernst-Planck theory, non-equilibrium steady state, electrolyte interface, Gouy-Chapman model Y1 - 2024 UR - https://doi.org/10.1088/1367-2630/ad19a9 VL - 26 IS - 1 SP - 013008 ER - TY - JOUR A1 - Engelmann, Bastian T1 - Towards Material-Batch-Aware Tool Condition Monitoring JF - Journal of Manufacturing and Materials Processing N2 - In subtractive manufacturing, process monitoring systems are used to observe the manufacturing process, to predict maintenance actions and to suggest process optimizations. One challenge, however, is that the observable signals are influenced not only by the degradation of the cutting tool, but also by deviations in machinability among material batches. Thus it is necessary to first predict the respective material batch before making maintenance decisions. In this study, an approach is shown for batch-aware tool condition monitoring using feature extraction and unsupervised learning to analyze high-frequency control data in order to detect clusters of materials with different machinability, and subsequently optimize the respective manufacturing process. This approach is validated using cutting experiments and implemented as an edge framework. KW - manufacturing KW - material Y1 - 2021 UR - https://doi.org/10.3390/jmmp5040103 SN - 2504-4494 VL - 5 IS - 4 ER - TY - JOUR A1 - Schmitt, Anna-Maria A1 - Engelmann, Bastian T1 - A Series Production Data Set for Five-Axis CNC Milling JF - Data N2 - The described data set contains features from the machine control of a five-axis milling machine. The features were recorded during thirteen series productions. Each series production includes a changeover process in which the machine was set up for the production of a different product. In addition to the timestamps and the twenty recorded features derived from Numerical Control (NC) variables, the data set also contains labels for the different production phases. For this purpose, up to 23 phases were assigned, which are based on a generalized milling process. The data set consists of thirteen .csv files, each representing a series production. The data set was recorded in a production company in the contract manufacturing sector for components with real series orders in ongoing industrial production. Y1 - 2024 U6 - https://doi.org/10.3390/data9050066 SN - 2306-5729 VL - 9 IS - 5 PB - MDPI ER - TY - JOUR A1 - Schmitt, Anna-Maria A1 - Engelmann, Bastian T1 - A Series Production Data Set for Five-Axis CNC Milling JF - Data Y1 - 2024 UR - https://doi.org/10.3390/data9050066 VL - 2024 IS - 9 SP - 1 EP - 9 ER - TY - JOUR A1 - Vahrenhold, Jan Richard A1 - Brandmeier, Melanie A1 - Müller, Markus Sebastian T1 - MMTSCNet: Multimodal Tree Species Classification Network for Classification of Multi-Source, Single-Tree LiDAR Point Clouds JF - Remote Sensing N2 - Trees play a critical role in climate regulation, biodiversity, and carbon storage as they cover approximately 30% of the global land area. Nowadays, Machine Learning (ML)is key to automating large-scale tree species classification based on active and passive sensing systems, with a recent trend favoring data fusion approaches for higher accuracy. The use of 3D Deep Learning (DL) models has improved tree species classification by capturing structural and geometric data directly from point clouds. We propose a fully Multimodal Tree Species Classification Network (MMTSCNet) that processes Light Detection and Ranging (LiDAR) point clouds, Full-Waveform (FWF) data, derived features, and bidirectional, color-coded depth images in their native data formats without any modality transformation. We conduct several experiments as well as an ablation study to assess the impact of data fusion. Classification performance on the combination of Airborne Laser Scanning (ALS) data with FWF data scored the highest, achieving an Overall Accuracy (OA) of nearly 97%, a Mean Average F1-score (MAF) of nearly 97%, and a Kappa Coefficient of 0.96. Results for the other data subsets show that the ALS data in combination with or even without FWF data produced the best results, which was closely followed by the UAV-borne Laser Scanning (ULS) data. Additionally, it is evident that the inclusion of FWF data provided significant benefits to the classification performance, resulting in an increase in the MAF of +4.66% for the ALS data, +4.69% for the ULS data under leaf-on conditions, and +2.59% for the ULS data under leaf-off conditions. The proposed model is also compared to a state-of-the-art unimodal 3D-DL model (PointNet++) as well as a feature-based unimodal DL architecture (DSTCN). The MMTSCNet architecture outperformed the other models by several percentage points, depending on the characteristics of the input data. Y1 - 2025 U6 - https://doi.org/https://doi.org/10.3390/rs17071304 SN - 2072-4292 VL - 17 IS - 7 PB - MDPI AG ER - TY - JOUR A1 - Schweighart, Roxana A1 - O'Sullivan, Julie Lorraine A1 - Klemmt, Malte A1 - Teti, Andrea A1 - Neuderth, Silke T1 - Wishes and needs of nursing home residents BT - a scoping review JF - healthcare N2 - Falling birth rates and rising life expectancy are leading to global aging. The proportional increase in older people can be observed in almost all countries and regions worldwide. As a result, more people spend their later years in nursing homes. In homes where person-centered care is implemented, residents report greater satisfaction and quality of life. This approach is based on the wishes and needs of the residents. Therefore, the purpose of this scoping review is to explore the wishes and needs of nursing home residents. A scoping review of the literature was conducted in which 12 databases were systematically searched for relevant articles according to PRISMA-ScR guidelines. Both quantitative and qualitative study designs were considered. A total of 51 articles met the inclusion criteria. Included articles were subjected to thematic analysis and synthesis to categorize findings into themes. The analysis identified 12 themes to which the wishes and needs were assigned: (1) Activities, leisure, and daily routine; (2) Autonomy, independence, choice, and control; (3) Death, dying, and end-of-life; (4) Economics; (5) Environment, structural conditions, meals, and food; (6) Health condition; (7) Medication, care, treatment, and hygiene; (8) Peer relationship, company, and social contact; (9) Privacy; (10) Psychological and emotional aspects, security, and safety; (11) Religion, spirituality; and (12) Sexuality. Nursing home residents are not a homogeneous group. Accordingly, a wide range of needs and wishes are reported in the literature, assigned to various topics. This underscores the need for tailored and person-centered approaches to ensure long-term well-being and quality of life in the nursing home care setting. KW - quality of life KW - well-being KW - long-term care Y1 - 2023 UR - https://doi.org/10.3390/healthcare10050854 SN - 2227-9032 VL - 10 IS - 5 ER - TY - JOUR A1 - George Biju, Vinai A1 - Schmitt, Anna-Maria A1 - Engelmann, Bastian T1 - Assessing the Influence of Sensor-Induced Noise on Machine-Learning-Based Changeover Detection in CNC Machines JF - Sensors Y1 - 2024 UR - https://doi.org/10.3390/s24020330 VL - 2024 ER - TY - JOUR A1 - Hofmann, Alexander A1 - Heusinger, Marc T1 - Cost-oriented sensor concept for magnetostrictive force measurement and its material requirements JF - Journal of Sensors and Sensor Systems N2 - Ferromagnetic materials change their magnetic properties under load, enabling the implementation of a force sensor. The magnetic field emerging from such a sensor can be measured by secondary sensors to approximate the load acting on the sensor. A test setup simulating a potential application environment is described and its measurement results are presented. Furthermore, relevant magnetic material properties of an exemplarily chosen cold working steel are discussed. Y1 - 2025 U6 - https://doi.org/10.5194/jsss-14-47-2025 VL - 14 IS - 1 SP - 47 EP - 54 ER - TY - JOUR A1 - Yükselen, Emir A1 - Rahimpour, Ebrahim T1 - An improvement in the design process of sustainable peak power rating transformer for solar utility JF - International Journal of Electrical Power & Energy Systems N2 - The transformer industry faces critical challenges, such as maintaining reliable production while meeting rising sustainability requirements. This paper introduces a significant advancement in the design and optimization of a transformer dedicated to a photovoltaic power plant, which exhibits a unique loading cycle distinct from standard power and distribution transformers. The main aim is to minimize the carbon footprint by enhancing the design process to improve operational performance, efficiency, and functional reliability. Such upgrades are essential for transitioning to a zero-emission electricity system and developing green energy projects. In this paper, a transformer has been studied using a combination of electrical design and 3D finite element method simulation to evaluate various design parameters. An optimization study has been conducted using an innovative multi-objective genetic algorithm utilizing a cost function that factors in size and material costs to identify the most efficient and cost-effective design solutions. The proposed design method was then validated through thermal model simulations and experimental tests based on the photovoltaic load cycle. A comparison of critical thermal parameters directly affecting the transformer’s lifetime and reliability was also drawn. The results were consistent with the expected outcomes, confirming the effectiveness and reliability of the proposed design methodology. KW - Transformer KW - Photovoltaic KW - Finite element method KW - Optimization KW - Genetic algorithm Y1 - 2025 U6 - https://doi.org/https://doi.org/10.1016/j.ijepes.2025.110928 SN - 0142-0615 VL - 170 SP - 1 EP - 13 PB - Elsevier BV ER -